40,486 research outputs found

    The role of big data in smart city

    No full text
    The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequency identification, and Bluetooth in the real-world environment using highly networked services. The combination of the IoT and big data is an unexplored research area that has brought new and interesting challenges for achieving the goal of future smart cities. These new challenges focus primarily on problems related to business and technology that enable cities to actualize the vision, principles, and requirements of the applications of smart cities by realizing the main smart environment characteristics. In this paper, we describe the existing communication technologies and smart-based applications used within the context of smart cities. The visions of big data analytics to support smart cities are discussed by focusing on how big data can fundamentally change urban populations at different levels. Moreover, a future business model that can manage big data for smart cities is proposed, and the business and technological research challenges are identified. This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data

    Performance assessment of RDF graph databases for smart city services

    Get PDF
    Abstract Smart cities are providing advanced services aggregating and exploiting data from different sources. Cities collect static data such as road graphs, service description, as well as dynamic/real time data like weather forecast, traffic sensors, bus positions, city sensors, events, emergency data, flows, etc. RDF stores may be used to set up knowledge bases integrating heterogeneous information for web and mobile applications to use the data for new advanced services to citizens and city administrators, thus exploiting inferential capabilities, temporal and spatial reasoning, and text indexing. In this paper, the needs and constraints for RDF stores to be used for smart cities services, together with the currently available RDF stores are evaluated. The assessment model allows a full understanding of whether an RDF store is suitable to be used as a basis for Smart City modeling and applications. The RDF assessment model is also supported by a benchmark which extends available RDF store benchmarks at the state the art. The comparison of the RDF stores has been applied on a number of well-known RDF stores as Virtuoso, GraphDB (former OWLIM), Oracle, StarDog, and many others. The paper also reports the adoption of the proposed Smart City RDF Benchmark on the basis of Florence Smart City model, data sets and tools accessible as Km4City Http://www.Km4City.org , and adopted in the European Commission international smart city projects named RESOLUTE H2020, REPLICATE H2020, and in Sii-Mobility National Smart City project in Italy

    Smart cities: a policy tool for city efficiency?

    Get PDF
    The level of interest in smart cities has been growing during these last years. The academic literature (Hollands, 2008; Caragliu et al., 2009, Nijkamp et al., 2011 and Lombardi et al., 2012) has identified a number of factors that characterise a city as smart, such as economic development, business-friendly, environmental sustainability, social innovation, information and knowledge process, and human and social capital. Thus, the smartness concept is strictly linked to urban efficiency in a multifaceted way as well as to citizens’ wellbeing through the use of appropriate technologies. Instead, from a “political perspective” smartness is mainly related to the ability of using ICT as instrument to strengthen economic growth. A research by Giffinger et al. (2007) to support European policy has defined the concept of smart city on the basis of several intangible indicators (such as a smart economy, smart mobility, smart environment, smart people, smart living, and smart governance) and has become a benchmark for European policy makers (European Parliament’s Committee on Industry, Research and Energy, 2014). Following this influential research, the aim of our paper is to verify how much that smartness definition can influence the efficiency and indirectly the growth of the cities. Using the concept of output maximising, we built a stochastic frontier function in terms of urban productivity and/or urban efficiency by assessing the economic distance that separates cities from that frontier. Our conclusions highlight that not all the six indicators defined in the Giffinger et al. (2007)’ analysis contribute to strength the city efficiency

    Developing an Approach to Measure Smartness and Sustainability of Ukrainian Cities

    Get PDF
    The article is aimed to review international and national frameworks which measure smartness and sustainability of cities in order to suggest an approach for measuring smartness and sustainability of Ukrainian cities. In research we have considered several definitions of Smart Sustainable cities (SSC) and components included by different scholars. Based on the selected international indexes we have created a comparison table of components grouped within 4 dimensions: Smart People, Smart Economy, Smart Environment, representing triple bottom line and Smart Governance along with ICTs as a supporting tool. For Ukrainian cities framework we have outlined two stages and several dimensions within each of the stages: a) creating conditions for concept building; b) actual measurement of the sustainability and smartness of cities. The further research should contribute to actual Smart city index establishment that will serve as a comparison and benchmark tool on the national level

    Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

    Get PDF
    The development of pervasive communication devices and the emergence of the Internet of Things (IoT) have acted as an essential part in the feasibility of smart city initiatives. Wireless sensor network (WSN) as a key enabling technology in IoT offers the potential for cities to get smatter. WSNs gained tremendous attention during the recent years because of their rising number of applications that enables remote monitoring and tracking in smart cities. One of the most exciting applications of WSNs in smart cities is detection, monitoring, and tracking which is referred to as object tracking sensor networks (OTSN). The adaptation of OTSN into urban cities brought new exciting challenges for reaching the goal of future smart cities. Such challenges focus primarily on problems related to active monitoring and tracking in smart cities. In this paper, we present the essential characteristics of OTSN, monitoring and tracking application used with the content of smart city. Moreover, we discussed the taxonomy of OTSN along with analysis and comparison. Furthermore, research challenges are investigated concerning energy reservation, object detection, object speed, accuracy in tracking, sensor node collaboration, data aggregation and object recovery position estimation. This review can serve as a benchmark for researchers for future development of smart cities in the context of OTSN. Lastly, we provide future research direction
    • …
    corecore